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鉴定 N6-甲基腺苷相关 lncRNA 用于人类免疫缺陷病毒感染者的结核病诊断。

Identification of N6-methylandenosine-related lncRNA for tuberculosis diagnosis in person living with human immunodeficiency virus.

机构信息

Drug Clinical Trial Center, Gansu Wuwei Tumor Hospital, 16 Xuanwu Road, Wuwei, Gansu, PR China.

Drug Clinical Trial Center, Gansu Wuwei Tumor Hospital, 16 Xuanwu Road, Wuwei, Gansu, PR China.

出版信息

Tuberculosis (Edinb). 2023 May;140:102337. doi: 10.1016/j.tube.2023.102337. Epub 2023 Mar 21.

DOI:10.1016/j.tube.2023.102337
PMID:36965224
Abstract

Development of a robust diagnostic test for patients co-infected with human immunodeficiency virus and tuberculosis (HIV/TB) is urgently needed. We believe N6-methyladenosine (m6A)- related long non-coding RNA (lncRNAs) from the host blood could be utilized to diagnose patients co-infected with HIV/TB. In this study, differentially expressed analysis, correlation analysis, univariate logistic regression, and logistic regression with least absolute shrinkage and selection operator (LASSO) were performed in RNA-Seq dataset containing of 14 HIV/TB co-infected subjects and 11 HIV mono-infected subjects. In total, five m6A related-lncRNAs with powerful diagnostic significance for HIV/TB co-infection were identified. We then built a deep learning model based on the five m6A related-lncRNAs for accurately discriminating the HIV/TB co-infected patients from HIV mono-infected patients with an accuracy of 92.0%, a sensitivity of 92.9%, a specificity of 90.9%, and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.935. Moreover, the diagnostic performance was validated in an external cohort containing 15 HIV/TB co-infected subjects and 16 HIV mono-infected subjects of whole blood. Overall, the findings showed that deep learning model based on five m6A-related lncRNAs had a worthy diagnostic performance for HIV/TB co-infection, and these diagnostic lncRNAs associated with m6A regulator genes could play a potential role in the pathogenesis of HIV/TB co-infection.

摘要

开发一种针对人类免疫缺陷病毒和结核病(HIV/TB)合并感染患者的稳健诊断检测方法迫在眉睫。我们认为宿主血液中的 N6-甲基腺苷(m6A)相关长非编码 RNA(lncRNA)可用于诊断 HIV/TB 合并感染患者。在这项研究中,我们对包含 14 名 HIV/TB 合并感染患者和 11 名 HIV 单感染患者的 RNA-Seq 数据集进行了差异表达分析、相关性分析、单变量逻辑回归和具有最小绝对收缩和选择算子(LASSO)的逻辑回归分析。总共鉴定出了 5 个具有强大 HIV/TB 合并感染诊断意义的 m6A 相关 lncRNA。然后,我们基于这 5 个 m6A 相关 lncRNA 构建了一个深度学习模型,用于准确区分 HIV/TB 合并感染患者和 HIV 单感染患者,其准确率为 92.0%,灵敏度为 92.9%,特异性为 90.9%,受试者工作特征(ROC)曲线下面积(AUC)为 0.935。此外,我们还在包含 15 名 HIV/TB 合并感染患者和 16 名 HIV 单感染患者的全血外部队列中验证了该模型的诊断性能。总的来说,研究结果表明,基于五个 m6A 相关 lncRNA 的深度学习模型对 HIV/TB 合并感染具有很好的诊断性能,这些与 m6A 调节基因相关的诊断 lncRNA 可能在 HIV/TB 合并感染的发病机制中发挥潜在作用。

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